Anthropic
AI Frontier · AI lab
- HQ
- San Francisco, US
- Founded
- 2021
- Size
- 1,500+
- Website
- anthropic.com
- Blog
- anthropic.com
Products
Currently tracking 127 active AI roles, down 32% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $46k–$850k (avg $406k).
Anthropic currently has 151 active AI-related job listings, with a significant focus on roles related to agents, which constitute 32% of their openings. Engineering is the most frequent function, followed by Research. The majority of their hiring is concentrated in the United States. Frequent technical tags include evals, model_serving, and agent_orchestration, suggesting a focus on the practical deployment and management of AI systems.
AI Frontier · AI lab
Anthropic currently has 149 active AI-related roles in our index. The most common open titles are: Regional Research Economist, Economic Research (2), Research Engineer, Machine Learning (RL Velocity) (2), Research Engineer, Production Model Post-Training (2), Staff Software Engineer, AI Reliability Engineering (2), Product Manager, Safeguards Rare Harms. Most positions are in Engineering and Research.
Anthropic's active AI hiring is concentrated in: agents (31%), serving infrastructure (15%), post-training (15%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Anthropic is hiring AI talent in: United States (130 roles), United Kingdom (18 roles), Canada (6 roles), Ireland (3 roles).
Job postings at Anthropic most frequently mention: Machine Learning, AI Safety, Production ML Systems, System Design, Large Language Models (LLMs).
In the past 30 days, Anthropic has posted 32 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Research Engineer, Machine Learning (RL Velocity) Research Engineer focused on building and improving the RL training infrastructure and tooling at Anthropic. The role involves identifying and removing bottlenecks in the RL stack, partnering with researchers and other engineering teams, and owning the reliability and performance of research runs to enable faster iteration and shipping of better models at scale. | DataPost-train | 9 |
| Software Engineer, RL Data Software Engineer on the RL Data team responsible for building systems that produce high-quality reinforcement learning data for Claude. This includes data collection pipelines, human feedback tooling, execution environments, and quality assurance. The role involves end-to-end ownership of stack components, iterating on prompts and evals, developing QA frameworks, hardening execution environments, and collaborating with domain experts and operations partners. |
| DataPost-train |
| 8 |
| Full-Stack Software Engineer, Reinforcement Learning Full-Stack Software Engineer to build platforms, tools, and interfaces for environment creation, data collection, and training observability for RL. The role involves owning product surfaces end-to-end, iterating on data collection strategies, and partnering with researchers to ship reliable products. | DataEval Gate | 8 |
| Staff+ Software Engineer, Privacy Staff+ Software Engineer, Privacy at Anthropic. This role focuses on establishing and leading the privacy engineering function for AI systems, architecting privacy-preserving systems, implementing privacy-enhancing technologies, and providing technical leadership. It involves working at the intersection of privacy engineering, AI safety, and distributed systems, with responsibilities including designing privacy-preserving architectures for training and inference, building privacy infrastructure, translating regulations into technical implementations, and leading privacy reviews. The role requires experience with privacy engineering principles, Python/Go, production systems at scale, data governance, and privacy regulations. | DataServe | 7 |